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Record W2129704808 · doi:10.1186/2046-2395-1-9

Caffeine extends life span, improves healthspan, and delays age-associated pathology in Caenorhabditis elegans

2012· article· en· W2129704808 on OpenAlexaff
George L. Sutphin, Emma Bishop, Melana E. Yanos, Richard Moller, Matt Kaeberlein

Bibliographic record

VenueLongevity & Healthspan · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics, Aging, and Longevity in Model Organisms
Canadian institutionsInstitute of Aging
FundersNational Institute on AgingNational Institutes of HealthEllison Medical Foundation
KeywordsLongevityCaffeineDiseaseCaenorhabditis elegansModel organismLife spanBiologyMechanism (biology)Psychological interventionDrugPhysiologyMedicineGeneticsPharmacologyEvolutionary biologyInternal medicinePsychiatryGeneEndocrinology

Abstract

fetched live from OpenAlex

BACKGROUND: The longevity of an organism is influenced by both genetic and environmental factors. With respect to genetic factors, a significant effort is being made to identify pharmacological agents that extend life span by targeting pathways with a defined role in the aging process. On the environmental side, the molecular mechanisms responsible for the positive influence of interventions such as dietary restriction are being explored. The environment experienced by humans in modern societies already contains countless compounds that may influence longevity. Understanding the role played by common compounds that substantially affect the aging process will be critical for predicting and interpreting the outcome of introducing new interventions. Caffeine is the most widely used psychoactive drug worldwide. Prior studies in flies, worms, and mice indicate that caffeine may positively impact age-associated neurodegenerative pathology, such as that observed in Alzheimer's disease. RESULTS: Here we report that caffeine is capable of extending life span and improving healthspan in Caenorhabditis elegans, a finding that is in agreement with a recently published screen looking for FDA-approved compounds capable of extending worm life span. Life span extension using caffeine displays epistatic interaction with two known longevity interventions: dietary restriction and reduced insulin signaling. Caffeine treatment also delays pathology in a nematode model of polyglutamine disease. CONCLUSIONS: The identification of caffeine as a relevant factor in aging and healthspan in worms, combined with prior work in both humans and rodents linking caffeine consumption to reduced risk of age-associated disease, suggests that caffeine may target conserved longevity pathways. Further, it may be important to consider caffeine consumption when developing clinical interventions, particularly those designed to mimic dietary restriction or modulate insulin/IGF-1-like signaling. The positive impact of caffeine on a worm model of polyglutamine disease suggests that chronic caffeine consumption may generally enhance resistance to proteotoxic stress and may be relevant to assessing risk and developing treatments for human diseases like Alzheimer's and Huntington's disease. Future work addressing the relevant targets of caffeine in models of aging and healthspan will help to clarify the underlying mechanisms and potentially identify new molecular targets for disease intervention.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.273
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.013
GPT teacher head0.257
Teacher spread0.244 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations76
Published2012
Admission routes1
Has abstractyes

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